Publications

Journal Papers

• Lavagna, L., Carillo, S., & Panella, M.
  A topical review on time-independent perturbation theory in one-dimensional quantum systems.
  Physica Scripta, 100 (10), 1–33, 2025.
  https://doi.org/10.1088/1402-4896/ae0a8f
  Keywords: one-dimensional quantum systems; perturbation theory; quantum computing.

• Lavagna, L., Piperno, S., Ceschini, A., & Panella, M.
  Small graph perturbations, QAOA, and the MaxCut problem.
  AVS Quantum Science, 1–14, 2025.
  Publisher: AIP Publishing; AVS Science and Technology of Materials, Interfaces and Processing.
  ISSN: 2639-0213.
  Keywords: quantum approximate optimization algorithm; MaxCut problem; graph perturbations; quantum computing.

• Buttitta, G., Lavagna, L., Bonacorsi, S., Barbarito, C., Moliterno, M., Saito, G., Oddone, I., Verdone, G., Raimondi, S., & Panella, M.
  Machine Learning-Guided microfluidic optimization of clinically inspired liposomes for nanomedicine applications.
  International Journal of Pharmaceutics, 686, 126362, 2025.
  https://doi.org/10.1016/j.ijpharm.2025.126362
  Keywords: machine learning; artificial intelligence; liposomes; microfluidics; nanomaterial; nanomedicine.

Conference Papers

• Ceschini, A., Lavagna, L., De Falco, F., Rosato, A., & Panella, M.
  Convergenza e generalizzazione nelle reti neurali quantistiche.
  In Memorie ET2024, Gruppo Nazionale Ricercatori di Elettrotecnica, Italia, pp. 1–2, 2024.

• De Falco, F., Lavagna, L., Ceschini, A., Rosato, A., & Panella, M.
  Evolving hybrid quantum-classical GRU architectures for multivariate time series.
  In IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2024), IEEE Computer Society, pp. 1–6, 2024.
  https://doi.org/10.1109/MLSP58920.2024.10734792
  Keywords: multivariate time series; quantum computing; quantum gated recurrent units; quantum machine learning.

• De Falco, F., Piperno, S., Lavagna, L., Ceschini, A., Rosato, A., & Panella, M.
  Enhancing QAOA Ansatz via Multi-Parameterized Layer and Blockwise Optimization.
  In Proceedings of Quantum Techniques in Machine Learning (QTML 2024), pp. 1–3, 2024.

• Lavagna, L., Ceschini, A., Rosato, A., & Panella, M.
  A layerwise-multi-angle approach to fine-tuning the quantum approximate optimization algorithm.
  In Proceedings of the International Joint Conference on Neural Networks (IJCNN 2024), IEEE, pp. 1–6, 2024.
  https://doi.org/10.1109/IJCNN60899.2024.10650075
  Keywords: quantum approximate optimization algorithm; layerwise-multi-angle approach; quantum computing.

• Lavagna, L., De Falco, F., Piperno, S., Ceschini, A., Rosato, A., & Panella, M.
  Quantum Generative Modeling via Straightforward State Preparation.
  In Proceedings of Quantum Techniques in Machine Learning (QTML 2024), University of Melbourne, Melbourne, Australia, pp. 1–1, 2024.

• Piperno, S., Lavagna, L., De Falco, F., Ceschini, A., Rosato, A., Windridge, D., & Panella, M.
  Quantum Enhanced Knowledge Distillation.
  In Proceedings of Quantum Techniques in Machine Learning (QTML 2024), University of Melbourne, Melbourne, Australia, pp. 1–1, 2024.

• Ceschini, A., Lavagna, L., De Falco, F., Rosato, A., & Panella, M.
  Circuiti neurali quantistici per il processamento di grafi, immagini e serie temporali.
  In Memorie ET2025, Gruppo Nazionale Ricercatori di Elettrotecnica, Italia, pp. 1–2, 2025.

• Lavagna, L., Ceschini, A., Piperno, S., Casalbore, M., Rosato, A., & Panella, M.
  Soluzioni quantistico-classiche per ottimizzazione e rilevamento di anomalie.
  In Memorie ET2025, Gruppo Nazionale Ricercatori di Elettrotecnica, Italia, pp. 1–2, 2025.

• Rosato, A., Lavagna, L., & Panella, M.
  Integrazione del calcolo iperdimensionale nei circuiti digitali, nelle reti neurali e nelle architetture computazionali quantistiche.
  In Memorie ET2025, Gruppo Nazionale Ricercatori di Elettrotecnica, Italia, pp. 1–2, 2025.

• Lavagna, L., De Falco, F., Ceschini, A., Rosato, A., & Panella, M.
  Trade-offs in Cryptosystems by Boolean and Quantum Circuits.
  In Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS 2025), IEEE, pp. 1–5, 2025.
  https://doi.org/10.1109/ISCAS56072.2025.11043205
  Keywords: fault tolerance; circuits and systems; encryption; quantum mechanics; circuit theory.

• Lavagna, L., De Falco, F., & Panella, M.
  Quantum Hyperdimensional Computing for Pattern Completion.
  In Proceedings of Quantum Techniques in Machine Learning (QTML 2025), pp. 1–1, 2025.

• Lavagna, L., De Falco, F., & Panella, M.
  The Effectiveness of Classical and Hybrid Models for MaxCut problem.
  In Proceedings of Quantum Techniques in Machine Learning (QTML 2025), pp. 1–1, 2025.

• Lavagna, L., De Falco, F., & Panella, M.
  Is the QAOA the Ultimate Solution for the MaxCut problem?
  In Proceedings of Quantum Techniques in Machine Learning (QTML 2025), pp. 1–1, 2025.